Campus: NYC, Online
This 30-credit program offers a hands-on, project-driven curriculum designed to bridge technical innovation with practical application. Through interdisciplinary coursework and real-world projects, students develop the advanced skills needed to design and implement AI solutions that create meaningful impact across industries. Close collaboration with faculty and applied learning experiences prepares graduates to address complex organizational challenges using artificial intelligence technologies.
Throughout the program, students learn to apply AI-based solutions to real-world problems using foundational models and industry-standard tools. The curriculum emphasizes evaluating user needs, translating requirements into effective AI implementations, and collaborating ethically with diverse stakeholders during the planning and execution of projects. Students also develop the ability to communicate highly technical AI concepts to non-technical audiences across professional settings.
Courses are offered both on campus and online, providing flexibility for students while maintaining strong engagement with faculty and campus resources.
Entering students with limited or no previous background are required to take IS 612 Introduction to Coding and IS 613 Database Management Systems. These courses do not count toward the degree, however, grades earned are computed into the student's QPA.
| Code | Title | Credits |
|---|---|---|
| IS 612 | Introduction to Coding | 3 |
| IS 613 | Database Management Systems | 3 |
| Code | Title | Credits |
|---|---|---|
| IS 614 | Applied Artificial Intelligence | 3 |
| IS 680 | Data Science I: Introduction to Data Science and Visualization | 3 |
| IS 685 | Ethical Issues in Artificial Intelligence | 3 |
| IS 689 | Human-AI Interaction | 3 |
| IS 692 | Research Project Seminar | 3 |
| Total Credits | 15 | |
Students have the option to select a concentration or fulfill the remainder of their credits through individual elective courses.
| Code | Title | Credits |
|---|---|---|
| Human-Centric AI Concentration | ||
| IS 638 | Introduction to User Experience Design | 3 |
| IS 679 | Cognitive Science and Technology | 3 |
| CS 659 | Introduction to Human Computer Interaction | 3 |
| Data-Centric Artificial Intelligence Concentration | ||
| IS 683 | Data Engineering for AI | 3 |
| IS 684 | Web Mining | 3 |
| IS 669 | Big Data and Information Systems | 3 |
| Computational Intelligence Concentration | ||
| IS 682 | Data Science II: Data Mining Algorithms and Applications | 3 |
| CS 632Q | Topic: Introduction to Natural Language Processing | 3 |
| CS 671 | Computer Vision | 3 |
| Open Concentration | ||
Students who choose the Open Concentration should consult with their Academic Advisor to select individual courses available on the current academic schedule. Students must also meet the prerequisites for all courses. | ||
| Course 1 | 3 | |
| Course 2 | 3 | |
| Course 3 | 3 | |
| Code | Title | Credits |
|---|---|---|
| Open Elective | 3 | |
| Open Elective | 3 | |
| Suggested Electives for the MS in Applied Artificial Intelligence Include: | ||
| IS 668 | Foundation of Geographic Information Systems | 3 |
| IS 687 | Social and Collaborative Computing | 3 |
| IS 678 | Location Analytics and Web GIS | 3 |
| IS 688 | Location Analytics and GIS Research | 3 |
| IS 690E | Topic: Information Architecture | 3 |
| CYB 631 | Automating Information Security with Python and Shell Scripting | 3 |
| CYB 611 | Introduction to Cybersecurity | 3 |
| CYB 651 | Cyber Intelligence Analysis & Modeling | 3 |
| CYB 621 | Information Security Management | 3 |
| CS 608 | Algorithms and Computing Theory | 3 |
| CS 610 | Introduction to Parallel Computing | 3 |
| CS 655 | Pattern Recognition | 3 |
| CS 660 | Mathematical Foundations of Analytics | 3 |
| CS 677 | Machine Learning | 3 |
Total Credits: 30
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2022-2023 Undergraduate Catalog
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